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Revert "Add masked select api (#21172)" (#21456)

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This reverts commit 007c997572.
paddle_tiny_install
ruri 5 years ago committed by GitHub
parent 3706ea67f8
commit 94bef03539
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3 changed files with 1 additions and 127 deletions
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63
python/paddle/fluid/layers/nn.py
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@ -28,7 +28,7 @@ from ..framework import Variable, OpProtoHolder, in_dygraph_mode
from ..dygraph import base
from ..param_attr import ParamAttr
from .layer_function_generator import autodoc, templatedoc, _generate_doc_string_
from .tensor import concat, assign, fill_constant, zeros, cast
from .tensor import concat, assign, fill_constant, zeros
from . import utils
from .. import unique_name
from functools import reduce
@ -183,7 +183,6 @@ __all__ = [
'hard_swish',
'gather_tree',
'uniform_random',
'masked_select',
]
@ -13620,63 +13619,3 @@ def uniform_random(shape, dtype='float32', min=-1.0, max=1.0, seed=0):
outputs={"Out": out})
return helper.append_activation(out)
def masked_select(input, mask):
"""
This OP selects elements of the input tensor according to the mask tensor.
The shapes of the mask tensor don't have to match shapes of input tensor, but they must be broadcastable, and the result is a new 1-D tensor.
NOTE: The meaning of broadcastable is consistent with expand_as.
Parameters:
input(Variable): The input tensor, the data type should be int32, float32, float64.
mask(Variable): The boolean mask tensor, the data type should be bool.
Returns:
Variable: masked select tensor, its data type is same as the input.
Examples:
.. code-block:: python
import paddle.fluid as fluid
import numpy as np
mask_shape = [4,1]
shape = [4,4]
data = np.random.random(mask_shape).astype("float32")
input_data = np.random.randint(5,size=shape).astype("float32")
mask_data = data > 0.5
# print(input_data)
# [[0.38972723 0.36218056 0.7892614 0.50122297]
# [0.14408113 0.85540855 0.30984417 0.7577004 ]
# [0.97263193 0.5248062 0.07655851 0.75549215]
# [0.26214206 0.32359877 0.6314582 0.2128865 ]]
# print(mask_data)
# [[ True]
# [ True]
# [False]
# [ True]]
input = fluid.data(name="input",shape=[4,4],dtype="float32")
mask = fluid.data(name="mask",shape=[4,1],dtype="bool")
result = fluid.layers.masked_select(input=input, mask=mask)
place = fluid.CPUPlace()
exe = fluid.Executor(place)
start = fluid.default_startup_program()
main = fluid.default_main_program()
exe.run(start)
masked_select_result= exe.run(main, feed={'input':input_data, 'mask':mask_data}, fetch_list=[result])
# print(masked_select_result)
# [0.38972723 0.36218056 0.7892614 0.50122297 0.14408113 0.85540855
# 0.30984417 0.7577004 0.26214206 0.32359877 0.6314582 0.2128865 ]
"""
mask_cast = cast(x=mask, dtype=input.dtype)
mask_expand = expand_as(x=mask_cast, target_tensor=input)
mask_expand_cast_back_bool = cast(x=mask_expand, dtype="bool")
select = where(mask_expand_cast_back_bool)
result = gather_nd(input, select)
return result

11
python/paddle/fluid/tests/unittests/test_layers.py
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@ -1640,9 +1640,6 @@ class TestBook(LayerTest):
elif dtype == 'int64':
return np.random.randint(self._low_data_bound,
self._high_data_bound, shape).astype(dtype)
elif dtype == 'bool':
return np.random.randint(self._low_data_bound,
self._high_data_bound, shape).astype(dtype)
def _get_data(self,
name,
@ -2574,14 +2571,6 @@ class TestBook(LayerTest):
out = layers.square_error_cost(input=x, label=y)
return (out)
def make_masked_select(self):
with program_guard(fluid.default_main_program(),
fluid.default_startup_program()):
x = self._get_data(name="X", shape=[4, 4], dtype="float32")
y = self._get_data(name="Y", shape=[1, 4], dtype="bool")
out = layers.masked_select(input=x, mask=y)
return (out)
def test_dynamic_lstmp(self):
# TODO(minqiyang): dygraph do not support lod now
with self.static_graph():

54
python/paddle/fluid/tests/unittests/test_masked_select.py
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@ -1,54 +0,0 @@
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import print_function
import unittest
import numpy as np
import sys
import paddle.fluid.core as core
import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid.executor import Executor
class TestMaskedSelect(unittest.TestCase):
def test_masked_select(self):
mask_shape = [4, 1]
shape = [4, 4]
data = np.random.random(mask_shape).astype("float32")
input_data = np.random.random(shape).astype("float32")
mask_data = data > 0.5
mask_data_b = np.broadcast_to(mask_data, shape)
npresult = input_data[np.where(mask_data_b)]
input_var = layers.create_tensor(dtype="float32", name="input")
mask_var = layers.create_tensor(dtype="bool", name="mask")
output = layers.masked_select(input=input_var, mask=mask_var)
for use_cuda in ([False, True]
if core.is_compiled_with_cuda() else [False]):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
exe = Executor(place)
result = exe.run(fluid.default_main_program(),
feed={"input": input_data,
"mask": mask_data},
fetch_list=[output])
self.assertTrue(np.isclose(npresult, result).all())
if __name__ == "__main__":
unittest.main()
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